Growth doesn’t happen when a contract is signed. Growth happens when customers actually use what they bought, day after day. We wrap our usage-based sales series by connecting the dots between pricing strategy, operations, and compensation—showing a concrete path from “right to buy” to realized revenue you can bank on.

We start by reframing the sales motion for consumption models. Winning access is only the opening move; the real work is guiding adoption and hitting a clear, data-backed ramp. Rather than forcing usage into traditional opportunities, we walk through why account-level management creates clarity across products, regions, and divisions. From there, we dig into forecasting: finance or a deal desk should own usage predictions with analytics and machine learning, not sellers guessing run rate. You’ll learn how to stack committed volumes with live run rate to set honest targets and expose realization gaps before they become surprises.

Role design gets a reset too. AEs close the first purchase and stay accountable through the ramp window, then hand off to CSMs or AMs to maintain and deepen value while they open the next wedge—new divisions, higher tiers, or complementary products. We share practical ways to instrument telemetry, trigger alerts when adoption stalls, and align incentives to ramp and sustained usage. The result is a simple, repeatable operating model: forecast with data, manage at the account, pay for realization, and hunt for expansion where customers already show proof of value.

Ready to turn promises into proof and surface the growth hiding in your consumption revenue? Follow the show, share this episode with a teammate who owns forecasting or CS, and leave a quick review telling us your ramp window and how you define success.

Most comp plans buy the wrong behavior in a usage-based world—and the results show up as stale pipelines, noisy dashboards, and hunters who drift into farming. We sat down with seasoned sales ops leader Chuck Lee to unpack how to pay for outcomes that actually matter: a clean start, a predictable ramp, and a scalable hand-off that sticks.

We trace a real transformation inside a large inbound motion where reps were incentivized to chase the oldest leads and obsess over consumption they didn’t own. By stripping the plan to a simple, action-focused design and shutting off post-implementation pay for AEs, the team saw a 40%+ lift in conversion. Chuck explains why high-velocity sales demands fewer choices, not more; how to align quotas to volatile demand without eroding trust; and the telltale signs your plan is buying noise instead of revenue.

Then we go deep on usage-based mechanics. The true “deal won” is when the customer starts using the product, and the second milestone is the ramp to forecast. Chuck shares how to set the AE’s window in the deal using historical ramp curves, why FP&A should co-own the model, and how SLAs between sales and CS prevent credit confusion and dropped hand-offs. We also confront the perpetual commission trap that turns hunters into farmers, and outline a cleaner split: hunters own start and ramp-to-target, farmers own adoption, expansion, and problem-solving.

If you’re wrestling with comp design for usage-based sales, this conversation gives you practical guardrails, from monthly quota tuning and points-based payouts to role clarity that protects new logo growth. Subscribe, share with your revenue team, and tell us: what behavior is your comp plan really buying?

The loudest AI often isn’t the smartest. We dig into fresh research with Curtis Schroeder, Head of Research and Insight at Varicent, to unpack a striking pattern among 150 revenue leaders: most expect the biggest ROI from system-level AI—forecasting, territory design, quota setting, incentive modeling—while investments still chase seller-facing tools that look great in a demo but struggle to compound impact.

Curtis explains why AI for revenue is really two markets. Seller AI promises instant productivity stories yet demands training, process change, and continuous behavior shifts. System AI upgrades decision quality at the core, creating compounding gains across the org—better coverage, cleaner attainment, faster re-planning, and more credible forecasts. We explore how to separate hype from value, why human skepticism remains the top blocker, and why adoption improves when AI becomes invisible inside workflows rather than another tool reps must learn.

You’ll hear how leaders pair quick visible wins with deeper system investments, how to make forecasting an always-on signal rather than a month-end ritual, and how to link territory potential to quota for fairer, higher-yield plans. We also get real about ROI proof: attribution is messy, but speed, decision quality, and resilience to market shocks are measurable and persuasive. If you’re navigating mandates to “do AI” while chasing durable growth efficiency, this conversation offers a practical blueprint to build trust, compress planning cycles, and invest where results compound.

If the episode sparks ideas, follow the show, share it with a teammate, and leave a quick review—what’s one system-level decision you’d upgrade with AI next?

Download the report mentioned in this podcast:

https://www.varicent.com/info/ai-roi-sales-revops